Emergent Story Generation: Lessons from Improvisational Theater

An emergent approach to story generation by computer is characterized by a lack of predetermined plot and a focus on character interaction forming the material for stories. A potential problem is that no interesting story emerges. However, improvisational theater shows that – at least for human actors – a predetermined plot is not necessary for creating a compelling story. There are some principles that make a successful piece of improvisational theater more than a random interaction, and these principles may inform the type of computational processes that an emergent narrative architecture draws from. We therefore discuss some of these principles, and show how these are explicitly or implicitly used in story generation and interactive storytelling research. Finally we draw lessons from these principles and ask attention for two techniques that have been little investigated: believably incorporating directives, and late commitment

Organizational knowledge dynamics

The paper addresses the main issues concerning knowledge conceptualization and knowledge dynamics, in the context of Romanian organizations. The links between organizational knowledge, organizational learning and organizational culture are being investigated, with the aim of conceptual clarification and paradigm unification, in a domain of increasing research interest, where increasing complexity implies the risk of increasing confusion.knowledge dynamics, organizational learning, organizational intelligence, organizational culture.

Helping to stay aware!: MEM+ a computerised application for Alzheimer’s patients

Dementia is, unfortunately, a well-known problem of nowadays, product of a set of generational transformations and a result of better life conditions. Memory is the key factor in this type of illness and it is nuclear to understand how it is constructed to hypothesise and try to determine how it degenerates. In this paper, memory structures are presented as a starting point of the research and then based on what type of memories are more affected on Alzheimer’s patients an application has been devised: MEM+. This application aims at tracking the illness evolution and at the same time provide cognitive stimulus with a set of serious games. To devise a small prototype of the application a participatory design has been conducted.info:eu-repo/semantics/publishedVersio

Character Education using Pedagogical Agents and Socratic Voice

Promoting ethical, responsible, and caring young people is a perennial aim of education. Schools are invited to include moral teaching in every possible curriculum, such as the core subjects and sports teams and clubs. Efforts have been done to find other teaching ways other than traditional ones such as games or role play or engaging students in moral dilemmas. Computer games have been always found as one of the most engaging learning platforms. This paper introduces AEINS, a learning environment that is designed and implemented based on the learning theories such as: Bloom’s Taxonomy, Keller’s ARCS model and Gagné’s Nine Principles. The learning environment allows the students to interact with different moral dilemmas and see the effect of their choices on themselves and others. AEINS makes use of the Socratic Method as its predominant teaching pedagogy and employs pedagogical agents to supply the educational process. AEINS evaluation results indicated development of moral reasoning and transfer of moral virtues to its users

Facial actions as visual cues for personality

What visual cues do human viewers use to assign personality characteristics to animated characters? While most facial animation systems associate facial actions to limited emotional states or speech content, the present paper explores the above question by relating the perception of personality to a wide variety of facial actions (e.g., head tilting/turning, and eyebrow raising) and emotional expressions (e.g., smiles and frowns). Animated characters exhibiting these actions and expressions were presented to human viewers in brief videos. Human viewers rated the personalities of these characters using a well-standardized adjective rating system borrowed from the psychological literature. These personality descriptors are organized in a multidimensional space that is based on the orthogonal dimensions of Desire for Affiliation and Displays of Social Dominance. The main result of the personality rating data was that human viewers associated individual facial actions and emotional expressions with specific personality characteristics very reliably. In particular, dynamic facial actions such as head tilting and gaze aversion tended to spread ratings along the Dominance dimension, whereas facial expressions of contempt and smiling tended to spread ratings along the Affiliation dimension. Furthermore, increasing the frequency and intensity of the head actions increased the perceived Social Dominance of the characters. We interpret these results as pointing to a reliable link between animated facial actions/expressions and the personality attributions they evoke in human viewers. The paper shows how these findings are used in our facial animation system to create perceptually valid personality profiles based on Dominance and Affiliation as two parameters that control the facial actions of autonomous animated characters

Multispace behavioral model for face-based affective social agents

This paper describes a behavioral model for affective social agents based on three independent but interacting parameter spaces: knowledge, personality, andmood. These spaces control a lower-level geometry space that provides parameters at the facial feature level. Personality and mood use findings in behavioral psychology to relate the perception of personality types and emotional states to the facial actions and expressions through two-dimensional models for personality and emotion. Knowledge encapsulates the tasks to be performed and the decision-making process using a specially designed XML-based language. While the geometry space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios

Personality representation: predicting behaviour for personalised learning support

The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of application. More recent work on adaptive hypermedia has resolved some of these issues but has been criticised for the lack of support scope, focusing on learning paths and alternative content presentation. The student model used within these systems is also of limited scope and often based on learning history or learning styles.This research examines the potential of using a personality theory as the basis for a personalisation mechanism within an educational support system. The automated support system is designed to utilise a personality based profile to predict student behaviour. This prediction is then used to select the most appropriate feedback from a selection of reflective hints for students performing lab based programming activities. The rationale for the use of personality is simply that this is the concept psychologists use for identifying individual differences and similarities which are expressed in everyday behaviour. Therefore the research has investigated how these characteristics can be modelled in order to provide a fundamental understanding of the student user and thus be able to provide tailored support. As personality is used to describe individuals across many situations and behaviours, the use of such at the core of a personalisation mechanism may overcome the issues of scope experienced by previous methods.This research poses the following question: can a representation of personality be used to predict behaviour within a software system, in such a way, as to be able to personalise support?Putting forward the central claim that it is feasible to capture and represent personality within a software system for the purpose of personalising services.The research uses a mixed methods approach including a number and combination of quantitative and qualitative methods for both investigation and determining the feasibility of this approach.The main contribution of the thesis has been the development of a set of profiling models from psychological theories, which account for both individual differences and group similarities, as a means of personalising services. These are then applied to the development of a prototype system which utilises a personality based profile. The evidence from the evaluation of the developed prototype system has demonstrated an ability to predict student behaviour with limited success and personalise support.The limitations of the evaluation study and implementation difficulties suggest that the approach taken in this research is not feasible. Further research and exploration is required –particularly in the application to a subject area outside that of programming

Fundamental processes in developing organizational intelligence

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